Contributions
Abstract: PB1814
Type: Publication Only
Session title: Thalassemias
Background
Anemia is a public health problem. Two etiologies of microcytic anemia are relatively common in our country: iron deficiency anemia (IDA) and minor β-thalassemia (βTM). To guide the clinician in discriminating IDA from βTM, several studies have developed indices and formulas based on cells blood count parameters determined by hematology analyzers.
Aims
The aim of our study was to study the performance of these formulas to discriminate βTM and IDA and to identify the cut-off values adapted to our population for each formula.
Methods
After reviewing the records of adult patients with IDA and βTM, two groups were formed (IDA (n=172) and βTM group (n=69)). Demographic and cells blood count data were recorded. Performances of ten formulas and indices reported in the literature in the discrimination between IDA and βTM were studied. Statistical analysis was performed using SPSS 19.0. Sensitivity, specificity, Likelihood ratios, predictive values and analysis of ROC curves were carried out. Optimal cut-off values were determined according to calculation of Youden Index (J).
Results
Among CBC parameters, the hemoglobin rate, the erythrocyte count and the IDR-SD parameter showed an excellent discriminating power (respectively; AUC= 0.913, 0.971 and 0.968). Performance assessment of the various original cut-off indices, three of them were reliable: Green King index (Se= 71.01%, Sp= 97.67%; AUC=0.96), RDWI (Se= 78.26%, Sp=97.67%; AUC=0.95), and Sirdah index (Se=76.81%, Sp=97.67%; AUC=0.965). At the new cut-off, the England and Fraser index, the Green King index, the Sirdah index and the RDWI were the most effective in diagnosing βTM. At these new thresholds, only England and Fraser index and Sirdah index showed a gain in sensitivity and accuracy.
Conclusion
The use of formulas and indices to distinguish βTM from IDA is a considerable decision support tool for the clinician, however the adoption of population-specific cut-offs helps to improve the performance of these formulas and indices. The technology deployed by hematology analyzers and some clinical data would be necessary for optimal diagnostic guidance.
Keyword(s): Anemia, Thalassemia
Abstract: PB1814
Type: Publication Only
Session title: Thalassemias
Background
Anemia is a public health problem. Two etiologies of microcytic anemia are relatively common in our country: iron deficiency anemia (IDA) and minor β-thalassemia (βTM). To guide the clinician in discriminating IDA from βTM, several studies have developed indices and formulas based on cells blood count parameters determined by hematology analyzers.
Aims
The aim of our study was to study the performance of these formulas to discriminate βTM and IDA and to identify the cut-off values adapted to our population for each formula.
Methods
After reviewing the records of adult patients with IDA and βTM, two groups were formed (IDA (n=172) and βTM group (n=69)). Demographic and cells blood count data were recorded. Performances of ten formulas and indices reported in the literature in the discrimination between IDA and βTM were studied. Statistical analysis was performed using SPSS 19.0. Sensitivity, specificity, Likelihood ratios, predictive values and analysis of ROC curves were carried out. Optimal cut-off values were determined according to calculation of Youden Index (J).
Results
Among CBC parameters, the hemoglobin rate, the erythrocyte count and the IDR-SD parameter showed an excellent discriminating power (respectively; AUC= 0.913, 0.971 and 0.968). Performance assessment of the various original cut-off indices, three of them were reliable: Green King index (Se= 71.01%, Sp= 97.67%; AUC=0.96), RDWI (Se= 78.26%, Sp=97.67%; AUC=0.95), and Sirdah index (Se=76.81%, Sp=97.67%; AUC=0.965). At the new cut-off, the England and Fraser index, the Green King index, the Sirdah index and the RDWI were the most effective in diagnosing βTM. At these new thresholds, only England and Fraser index and Sirdah index showed a gain in sensitivity and accuracy.
Conclusion
The use of formulas and indices to distinguish βTM from IDA is a considerable decision support tool for the clinician, however the adoption of population-specific cut-offs helps to improve the performance of these formulas and indices. The technology deployed by hematology analyzers and some clinical data would be necessary for optimal diagnostic guidance.
Keyword(s): Anemia, Thalassemia